research
∙
03/03/2023
X^3KD: Knowledge Distillation Across Modalities, Tasks and Stages for Multi-Camera 3D Object Detection
Recent advances in 3D object detection (3DOD) have obtained remarkably s...
share
research
∙
10/13/2022
X-Align: Cross-Modal Cross-View Alignment for Bird's-Eye-View Segmentation
Bird's-eye-view (BEV) grid is a common representation for the perception...
research
∙
06/01/2022
On the Choice of Data for Efficient Training and Validation of End-to-End Driving Models
The emergence of data-driven machine learning (ML) has facilitated signi...
research
∙
03/02/2022
Detecting Adversarial Perturbations in Multi-Task Perception
While deep neural networks (DNNs) achieve impressive performance on envi...
research
∙
03/02/2022
Continual BatchNorm Adaptation (CBNA) for Semantic Segmentation
Environment perception in autonomous driving vehicles often heavily reli...
research
∙
04/12/2021
Improving Online Performance Prediction for Semantic Segmentation
In this work we address the task of observing the performance of a seman...
research
∙
04/09/2021
SVDistNet: Self-Supervised Near-Field Distance Estimation on Surround View Fisheye Cameras
A 360 perception of scene geometry is essential for automated driving, n...
research
∙
11/17/2020
Unsupervised BatchNorm Adaptation (UBNA): A Domain Adaptation Method for Semantic Segmentation Without Using Source Domain Representations
In this paper we present a solution to the task of "unsupervised domain ...
research
∙
08/10/2020
SynDistNet: Self-Supervised Monocular Fisheye Camera Distance Estimation Synergized with Semantic Segmentation for Autonomous Driving
State-of-the-art self-supervised learning approaches for monocular depth...
research
∙
07/14/2020
Self-Supervised Monocular Depth Estimation: Solving the Dynamic Object Problem by Semantic Guidance
Self-supervised monocular depth estimation presents a powerful method to...
research
∙
06/15/2020
Self-Supervised Domain Mismatch Estimation for Autonomous Perception
Autonomous driving requires self awareness of its perception functions. ...
research
∙
05/12/2020
Class-Incremental Learning for Semantic Segmentation Re-Using Neither Old Data Nor Old Labels
While neural networks trained for semantic segmentation are essential fo...
research
∙
04/23/2020
